ZAPINNER

Entity Resolution API

Clusters records that refer to the same real-world entity and emits one canonical record per entity. Reuses the deterministic dedupe engine for clustering and the shared merge engine for the canonical record. Billed per record.

What it does

Cluster records into entities and emit one canonical record each.

When to use it

Reach for Entity Resolution when you need to answer: “Which records are the same entity?” It sits in the Reconcile stage of the catalog — match expected against actual.

Endpoint & cost

POST /api/v1/entity-resolution

Cost: Per credit. Zaps draw down your shared monthly allowance; requests that fail validation are not charged.

Authentication

Send your key as a bearer token: Authorization: Bearer zap_live_…. See Authentication for key management and the alternate header.

Example request

curl https://zapinner.com/api/v1/entity-resolution \
  -H "Authorization: Bearer zap_live_••••••" \
  -H "Content-Type: application/json" \
  -d '{"records":[{"email":"a@acme.com","name":"Acme"},{"email":"A@ACME.com","name":"ACME Inc"}]}'
Every response is structured JSON and includes a request_id. Full field-level request and response schemas for this endpoint live in the OpenAPI spec and the API reference.

Errors & limits

Errors use one consistent shape ( error.code, error.message, request_id). See Errors and Rate limits.

SDK

Entity Resolution has typed methods in both the JavaScript and Python SDKs. Both are implemented and package-ready but not yet published to npm / PyPI — until they ship, vendor the package source or install from a git ref, or call the endpoint over HTTPS with the example above.

Try it

Select Entity Resolution in the playground to see the request, or run it live with your API key.

Related APIs

  • Reconciliation — Compare two datasets and surface mismatches, duplicates, and missing records.
  • Conflicts — Find fields whose values disagree across records sharing a key.
  • Merge — Collapse duplicate records into one golden record with provenance.
  • Survivorship — Collapse keyed groups into golden records with survivorship rules.
  • Similarity — Score pairwise similarity within one record set.
  • Link — Record linkage across two datasets.